Energy Conservation Technologies Research Articles

Reusable saturated synthesis solutions for compact zeolite membranes

Zeolite membranes have excellent application prospects in the separation of mixtures with molecular-level differences; however, the uneven distribution of active ingredients on the support causes defects in the zeolite membranes, limiting their industrial applications. In this study, compact NaX and NaA zeolite membranes with perfect pervaporation performance were prepared in reusable saturated membrane synthesis solutions. These saturated membrane synthesis solutions not only provided sufficient Si/Al components for the even growth of zeolite on the support, but also reduced the random deposition of zeolite particles on the support by reducing the formation of zeolite particles in the bulk solution, improving the quality of the resulting zeolite membranes. The separation factors of the obtained NaA and NaX zeolite membranes were greater than 10000 for the water/ethanol and methanol/MTBE mixtures, respectively. Moreover, the saturated synthesis solutions could be reused multiple times to synthesize zeolite membranes after nutrient supplementation, saving resources and reducing environmental pollution. This study presents reusable solutions for synthesizing compact zeolite membranes, promoting the development of membrane technology for environmental protection and energy conservation.

Uncertainty quantification of exchange efficiency in membrane-based air-to-air energy exchanger cores: Repetitive manufacturing and experiments

Air-to-air membrane-energy exchangers have been widely used in green buildings as passive energy-recovery technologies for energy conservation and carbon reduction. An air-to-air membrane-energy exchanger conserves building energy by forcing the indoor exhaust air and unconditioned fresh air to exchange heat and moisture. As a critical performance indicator, the energy-exchange efficiency is primarily determined by the core. To improve energy-saving performance, many studies have been conducted to analyze and enhance the efficiency of air-to-air membrane-energy exchanger cores by manufacturing, testing, modeling, and comparing different cores. However, few studies have investigated the uncertainty introduced by the manufacturing and testing processes (most related research only studied the uncertainty of the sensible efficiency), which means that some positive results of those controlled trials are possibly owing to the manufacturing tolerance or testing errors, rather than real technical progress. This study addresses this problem by quantifying the efficiency uncertainty caused by manufacturing and testing processes. Three cores were produced using the same manufacturing process and materials, followed by identical experimental tests on their sensible, latent, and enthalpy efficiencies. Comparison results suggest that even when all variables are controlled, the differential enthalpy efficiency of two “identical” cores still vary from 0 % to 2 %. Variance of repetitive testing results of a certain core can afford an enthalpy efficiency of 4 % owing to a non-ideal experimental procedure. When manufacturing tolerances and experimental errors are considered simultaneously, the differential sensible efficiency among multiple “identical” cores is within 0–5%, whereas latent efficiency data in winter shows a significant variation of 5–10 % for “identical” cores. The contributions and conclusions of this study are as follows. The efficiency uncertainty caused by manufacturing and testing processes is non-negligible, particularly in latent efficiency. This phenomenon could alert researchers and engineers in this field to conduct repetitive manufacturing and testing while trying to modify/test/compare air-to-air membrane-energy exchanger cores. Because this study is based on a limited number of cores, the quantitative results of this study should be considered a non-universal reference, and a systematic benchmark must be established in the future.

A group decision-making method for technology selection of petrochemical enterprises

Selecting appropriate energy conservation and emission reduction technologies is essential for the sustainable developments of petrochemical enterprises. It usually involves experienced experts from multi-domain and thus can be regarded as a large-scale group decision-making problem. Existing methods assumed that different experts use the same linguistic term set following the same semantics to express their evaluation values, and derived the ranking of alternatives by an indirectly obtained group preference matrix. Such an approach may induce information loss. To avoid these defects, this study introduces a model based on rank centrality and expert differences to choose appropriate technologies for petrochemical enterprises. First, an attitude parameter is introduced into a linguistic scale function to unify different judgment benchmarks of experts regarding the same linguistic term. Next, a direct weight elicitation method based on rank centrality is developed to deduce the individual rank vector of alternatives. A grey clustering method based on the similarities of individual rank vectors is extended to cluster experts into small groups, and the silhouette coefficient is used to determine clusters weights. Afterwards, the rank vectors of alternatives corresponding to subgroups and the global rank vector are calculated by the weighted averaging operator. Alternatives are ranked by the rank vector of the global group. Finally, four technologies were evaluated by the model, and the preferred technology was identified. The findings indicate that the proposed technology selection model alleviates information loss, elevates group consensus level, and provides a perspective for petrochemical enterprises in search of energy conservation and emission reduction technologies.

How does green finance reduce China's carbon emissions by fostering green technology innovation?

Understanding the decarbonisation effect of green finance is essential for combating climate change. However, improper measurement of green financial development and an in-depth discussion of its influencing channels may underestimate this effect. Therefore, this study employed an indicator system for green finance with various dimensions and instruments. It utilized the generalised method of moments approach and conducted multiple two-step analysis to investigate data from China on green technology innovation channels, employing the Green Solow model. The empirical results confirm the significant effect of green financial development on decreasing CO2 emissions, mainly in Eastern and Central China. Among the components of green finance, green financial efficiency reduces CO2 emissions more effectively than green financial scale. The influencing channel analysis suggests that the decarbonisation effect of green finance occurs mainly by concurrently promoting energy conservation and energy substitution technologies. The study results have important policy implications for governments in formulating targeted technology policies to control CO2 emissions.

A CO2 removal technology based on mineral carbonation and the stability of product carbon storage in a cement matrix

Toward a decarbonized society, the cement industry is continuously striving to enforce energy conservation technologies and develop low-carbon cement. The use of mineral carbonation in the cement and concrete sector and the associated value chain are central in the carbon recycling system, and the importance of CO2 removal technologies has been recognized. This paper proposes a mineral direct air carbon capture and storage in product technology newly designed by a mineral carbon capture reactor through direct feeding of atmospheric CO2. Additionally, a novel concrete mix for use as CO2-storing (CDS) concrete is proposed. This mix contains recarbonates generated using treated water with high Ca content at a ready-mixed concrete plant. The CDS concrete, with a recarbonate content in the range of 2–10% of cement, exhibited very similar initial and mechanical properties compared with ordinary concrete. The CO2 release from the recarbonate in a cement matrix under acidic corrosion and the thermal decomposition were assessed, and the findings are discussed.

Optimization method for multi-process energy consumption in iron and steel enterprises under the coordinated use of comprehensive energy

Sustainable development goals, such as energy conservation, emission reduction, cost reduction, and efficiency enhancement, present pressing challenges for the iron and steel industry. Process optimization technology for efficient production, energy conservation, and consumption reduction in the steel manufacturing process is based on the coordination of material and energy flow. Therefore, this article takes the production process of a converter steelmaking plant as the object, considers the regulatory requirements of multi-process and multi constraint operation optimization under the cooperation of production organization and energy conservation and consumption reduction, and it explores a production scheduling optimization method for steelmaking plants oriented towards material flow and energy flow synergy. Based on the characteristics of the problem space, this study suggests a hybrid genetic algorithm with local search (MOHGALS) that employs both standard and advanced evolution techniques. Tests on concrete problems demonstrate that the MOHGALS approach yields a superior set of multi-objective Pareto schemes. Additionally, random-generated test cases were used to evaluate the algorithm’s performance. The outcomes show that MOHGALS performs better than competing algorithms on multi-objective evaluation indicators, and that the suggested improved evolution approach may effectively boost the algorithm’s performance.

Analysing the response of CO2 emissions to business cycle in a developing economy: evidence for South Africa post-apartheid era

Introduction: This research addresses the response of CO2 emissions to economic fluctuations in South Africa post-Apartheid, covering the period 1990–2018. While previous studies focused on developed countries, limited attention has been given to sub-Saharan developing nations. The study challenges the assumption of constant emissions elasticity in current forecasts.Methods: The study employs a two-step strategy. Firstly, the rolling window regression with Hodrick-Prescott filtering was used to investigate whether the CO2 emissions elasticity varies over time. Secondly, a Markov-switching approach was used to examine the regime-switching behavior in GDP.Results and Discussion: Results suggest that CO2 emisssions elasticity varies over time. This was confirmed through alternative filtering techniques (Christiano-Fitzgerald, Baxter King, and the Butterworth filter). Markov-switching analysis revealed a regime-switching behavior in GDP, indicating negative CO2 emissions elasticity during recessions and positive elasticity during expansions. These findings persist even when accounting for monetary policy shocks and productivity shocks in the Environmental Dynamic Stochastic General Equilibrium (E-DSGE) model. Noteworthy is that South Africa is among the top 20 greenhouse gas emitters globally.Conclusion and recommendations: The study recommends tailored carbon-pricing policies that are conscious to the countercyclical nature of business cycles. Pricing emissions higher during economic upswings aligns with periods of growth. Additionally, the government is advised to invest in research and development for energy conservation, efficiency, and renewable technologies to counterbalance emissions growth. Implementing emission caps and tax incentives can further enforce pollution abatement measures. Policymakers should consider these asymmetrical responses when addressing global warming challenges in South Africa.

Review and Recent Developments of Speed Regulation Technology for Energy Conservation Based on Permanent Magnet Adjustable Speed Drive

Review and Recent Developments of Speed Regulation Technology for Energy Conservation Based on Permanent Magnet Adjustable Speed Drive

A Study on the influence of China's green finance development on real estate prices

At present, the importance of green finance in the world market is becoming increasingly prominent. Various kinds of green products have emerged, and auxiliary policies have also come into being. China is one of the world's largest carbon dioxide emissions and the world's largest investor in new energy. In the face of severe environmental problems and challenges of sustainable development, the Chinese government attaches great importance to the development of green finance, and has adopted a series of positive policy documents and guidance, including the establishment of special funds, providing preferential fiscal and tax policies, and the establishment of a green bond market to promote its role in the financial system. In addition, China has set up a set of green financial standards and evaluation system to guide financial institutions and enterprises to be more transparent and sustainable in environmental risk management and green investment.
 The emergence of green finance has brought a certain impact on the real estate industry, a pillar industry of China's economy. At present, many people in China, especially in some central cities, have speculated on housing prices. This behavior has led to a speculative increase in the real estate market, a rapid rise in housing prices, an excessive consumption of resources, and the aggravation of social inequality. This conflicts the concept of sustainable development and environmental friendliness advocated by green finance. At the same time, the investment in green finance will squeeze out a part of the real estate market share. By directing investment in real estate to the flow of green buildings and energy conservation technologies, green finance can also promote the efficient use of resources and sustainable environmental development.
 Therefore, it is of great significance to deeply study the impact of green finance on real estate. By discussing the application of green finance in the real estate field, effective ways can be found to reduce the consumption of resources in the real estate industry, improve the energy efficiency of buildings, promote the development of green buildings, and guide China's real estate market towards the direction of sustainable development in practice. This is of great practical significance for realizing the dual goal of economic growth and environmental protection.
 Previous scholars have discussed a wide range of factors affecting real estate, including the monetary system, consumption level and so on. The related discussion on green finance also focuses on the impact of the ecological environment and some green products on the financial market. No scholar has specifically discussed the impact of green finance on real estate as a whole.
 Therefore, in order to ensure that the regression results are not affected by the economic turbulence during the epidemic period, this paper selects the relevant data of provinces and cities from 2008 to 2020 to regression the fixed effect model panel, conducts a study on the real estate price, and draws the following basic conclusions: green finance has a negative impact on the real estate price.
 The marginal contribution of this paper is the use of various green coefficient to build green financial index, to explore the influence of green finance as a whole, and make up the green finance influence the lack of the real estate research, to solve the current real estate investment market proportion and rising prices put forward new slow problems.
 The chapters of this paper are arranged as follows: the second part is the literature review, the third part is the experimental design and data, the fourth part is the empirical results, the fifth part is the robustness test, and the sixth part is the conclusion and policy suggestions.

Analysis of pressure interval/injection and production frequency on stability of large-scale supercritical CO2 storage in salt caverns

Carbon dioxide (CO2) is the primary greenhouse gas, with annual emissions reaching up to 54 billion tons globally, leading to an unprecedented acceleration of global warming. In conjunction with carbon capture, utilization, and storage (CCUS), which represents the most advanced and efficient technology for energy conservation and emission reduction, as well as the innovative concept of CO2 storage in salt caverns, this paper investigates the industrial application potential of supercritical CO2. Herein the feasibility of large-scale storage of supercritical CO2 in salt caverns was investigated, focusing on the stability aspect associated with such storage. Specifically concentrating on the impact of upper and lower injection/production pressures and frequencies on the stability of carbon storage in salt caverns, this study utilizes numerical simulation methods to simulate the creep process that occurs in China's bedded salt formations. Numerical simulation results showed that: 1) From the perspective of salt cavern stability, the volume shrinkage, creep and damage degree of surrounding rock during operation all fall within an acceptable range. Consequently, it is feasible to implement carbon storage in these salt caverns for a during of 100 years. 2) Shortening the range of internal pressure will enhance the stability of salt cavern for carbon storage. Furthermore, different pressure intervals have an impact on the creep concentration position within the cavern, primarily resulting in a transformation between internal contraction of surrounding rock and sediment accumulation caused by floor creep by altering the lower pressure limit. 3) The injection and production frequency of salt cavern carbon storage (SCCS) is characterized by a low occurrence rate (<10 cycles). The stability of the cavern can be enhanced by increasing the injection and production frequency, nevertheless, it is important to note that internal pressure remains the primary factor influencing cavern stability compared to the injection and production frequency.

A Concise Review of Nanoparticles Utilized Energy Storage and Conservation

Nanoparticles have revolutionized the landscape of energy storage and conservation technologies, exhibiting remarkable potential in enhancing the performance and efficiency of various energy systems. This review explores the versatile applications of nanoparticles in three key domains: battery technologies, supercapacitors, and solar energy conversion. In the realm of battery technologies, nanostructured particles have emerged as crucial catalysts and electrode materials, significantly elevating the energy density, cycling stability, and charge/discharge rates of batteries. By manipulating the surface chemistry and structure of nanoparticles, researchers have achieved breakthroughs in overcoming traditional limitations, paving the way for next-generation high-capacity and long-lasting batteries. The integration of tiny particles in supercapacitors has led to remarkable advancements in energy storage and rapid energy delivery. Nanoparticle-based electrodes have exhibited exceptional surface area, porosity, and conductivity, contributing to enhanced energy and power densities. The synergy of nanomaterials with novel electrolytes has also extended the operational lifespan of supercapacitors, addressing concerns regarding energy loss over cycles. Furthermore, nanoparticles have played a pivotal role in the field of solar energy conversion. In photovoltaics, nanoparticles with tailored optoelectronic properties have enabled improved light absorption, charge separation, and electron transport, ultimately boosting the efficiency of solar cells. Moreover, nanoparticles have been employed as catalysts in photocatalytic systems for solar fuel generation, driving the sustainable production of clean energy carriers. In this concise review, we highlight the recent advancements, challenges, and future prospects of nanoparticles in these critical energy domains. While the transformative impact of nanoparticles is evident, several challenges such as large-scale synthesis, cost-effectiveness, and long-term stability must be systematically addressed to ensure their seamless integration into practical energy applications. As researchers continue to explore novel synthesis techniques and innovative nanoarchitectures, nanoparticles are poised to reshape the energy landscape, accelerating the transition toward a more sustainable and efficient energy future.

Influence of dual-credit policy on the energy conservation and emission reduction technology R&D of Chinese auto industry

The dual-credit policy, as an important industrial policy in the automotive industry to replace fiscal subsidies, aims to achieve the dual objectives of energy conservation and emission reduction (ECER) and promote the development of new energy vehicles by establishing a dual credit system based on the average fuel consumption of conventional vehicles and credits for new energy vehicles. This paper employs a game model to investigate the differential impact of the dual-credit policy on ECER among automobile manufacturers with different industry structures. The study finds that the existing policy primarily favors manufacturers adopting the integration mode, followed by the multilateral mode and supply-monopoly mode respectively. Furthermore, R&D cost coefficient, unit price of credits, degree of competition and elasticity of cross-demand for fuel-saving functions are the four main factors that influence the profit model of the automobile industry. The findings of this study suggest that targeted policies need to be formulated for different industry structures during the adjustment of the policy in order to fully stimulate their enthusiasm for ECER. Additionally, the flexible combination of the four factors should be considered when formulating a specific dual-credit policy so as to achieve more energy saving and emission reduction effect in the automobile industry.

Optimized Low-Powered Wide Area Network within Internet of Things

The Internet of Things (IoT) is rapidly becoming an integral part of everyday life. LPWANs have been introduced to support the billions of internet-connected devices and the data they produce. LPWANs are capable of providing reliable connectivity even in low-density areas and devices consuming a low amount of energy. The exponential increase in the use of IoT applications across the globe will continue to generate more and more data traffic within the IoT network. Hence, it will increase device battery usage that may reduce the battery life expectancy limits. Thus, End Devices (EDs) within the IoT network in the near future will rise up to billions of devices operating in public, industry, and personal networks, generating a necessity for more correct and reliable energy conservation technology. This prompted the research work on an optimized low-powered wide area network within IoT. This paper focuses on three different strategies: LoRa power consumption model design, simulation of IoT wireless sensor networks, and implementation of SF allocation across the wireless sensor network and results analysis. The experiment has been carried out in various stages: firstly running a simulation over a wireless sensor network without optimization using MATLAB Simulink and obtaining the following result of 6.3997e-17 joules power consumption. Secondly, the authors test the network with power optimization using particle swarm optimization algorithms and obtained a better result of 2.5230e-17 joules. The LoRa energy consumption is reduced by 60%. Lastly, different simulation tests of LoRaWAN protocols with respect to throughput, packet loss, delay, data transmission, buffer size, and network density. The results presented on the graph showed that the proposed model outperforms the existing models. Hence, appropriate spreading factor allocation has increased the power efficiency of LoRa end device battery.

Simulation Analysis of a Novel Digital Pump with Direct Recycling of Hydraulic Energy

There is a permanent and strong need for energy recovery to improve the efficiency of the hydraulic system in the field of the construction machinery. In addition, the digital pump will become powerful and versatile by employing different configurations and intelligent control of the flow distribution valves. Considering this case, we have proposed a novel digital pump in which every plunger is equipped with two flow distribution valves. By controlling these two valves, external hydraulic energy can be directly reused without other components. Based on the structure and working principle of the digital pump, the mathematical model is established and three working modes are detailed. To verify the feasibility and correctness of control methods, a performance simulation testing platform including a digital pump, load module, hydraulic energy to be recovered, and controller module was developed in AMESim R15 software. The pressure, flow rate, and torque simulations of the digital pump in three working modes were carried out. The simulation results have shown that the digital pump not only can be used as an ordinary pump but also has the function of recovery and immediate reutilization of another hydraulic energy. Meanwhile, the corresponding variable displacement control strategy is effective and the positive torque required to drive the digital pump can be reduced, which verified the energy-saving of this scheme. The ideas and contents in this paper can offer significant references for energy conservation technology of various engineering machineries and the intensive study of digital hydraulics.

A practical method of carbon emission reduction ratio evaluation for expressway service area considering future infrastructures

A practical method of the carbon emission reduction ratio evaluation of expressway service areas considering future infrastructures is proposed to quantify the carbon emission reduction benefits of advanced power technologies. Taking an expressway service area in Guangxi as an example, based on its new infrastructure and low-carbon micro energy network construction scheme, the carbon emission reduction ratio of the service area is calculated and analyzed. The results show that the majority of carbon emissions in the expressway service area are contributed to electric carbon emissions, while little non-electric carbon emission exists, and there is little impact on the results if non-electric carbon emissions are neglected, which can also simplify the calculation process. This evaluation method takes into account both new loads brought by the new infrastructure and the improvement of the overall energy efficiency in the region by the advanced energy conservation and carbon reduction technologies. Emission reduction benefits can be quickly, intuitively and quantitatively achieved with advanced energy technologies such as distributed renewable energy, integrated energy system and AC/DC mixed supply. The error caused by simplified calculation is so small that is applicable to the early stage of project construction, predict and evaluate the carbon reduction benefits of advanced energy technologies to assist the orientation of the project.

Cloud-fog-based approach for smart wildfire monitoring

Wildfires have disturbed the delicate balance of the Earth's ecosystem, exacerbating global warming, floods, droughts, and causing a reduction in oxygen level. Early detection of wildfires is crucial in order to mitigate the risk of losses. The Internet of Things (IoT) has emerged as a critical tool in bridging disparate technologies, allowing for the real-time collection of data from sensors and further analysis of factors influencing the occurrence of wildfires (FIWs) on fog devices or cloud servers. However, most deployment of these sensor nodes in hostile and unmanned environments presents significant challenges to the reliability information collection of FIWs and the effectiveness of energy-conserving technologies. To address these challenges, this paper proposes a novel wildfire monitoring model based on an IoT-Fog-Cloud three-tier architecture. This model incorporates energy-conserving and fault-tolerant scheduling algorithms in the fog layer, ensuring that sensor nodes operate reliably. In the cloud layer, the multi-Grained Cascade Forest (GC-Forest) algorithm is utilized to analyze both spectral and FIWs data. Furthermore, in order to accurately assess the spread trend of forest fires, the Wang Zhengfei model is improved. Experimental results demonstrate that the energy-conserving algorithm reduces energy consumption by approximately 25.48%, while the fault-tolerant scheduling algorithm remains a fault detection rate of over 98.7%. The GC-Forest algorithm exhibits a low error rate of only 16.25%, with a hit rate of 83.75%, and a Hanssen-Kuiper skill score of 63.73%.

Polymer materials for solving actual problems of membrane gas

Membrane gas separation using polymeric membranes is one of rapidly developing energy-conserving technologies. This review describes the scope of membrane gas separation problems and demonstrates the relevance of membrane methods for their solution. The basic concepts and regularities of diffusion gas transfer and principles and characteristics of membrane gas separation are considered. The main physicochemical approaches to the selection of membrane materials considering both the properties of the gas–polymer system and the structure and physical properties of polymers are discussed. The considered issues are combined within a common approach to substantiate the choice of both existing commercial polymers and advanced polymeric materials to address important gas separation problems such as separation of air components; carbon dioxide, hydrogen and helium recovery from natural and industrial gas mixtures; and separation of a nitrogen and methane mixture. The avenues of development of the membrane materials science to solve each of the mentioned problems of membrane gas separation are demonstrated. The review is intended for specialists in the synthesis and physics of polymers for planning the research and assessing the applicability of polymeric materials for various practical gas separation problems and for specialists in the membrane materials science and membrane technology. &lt;br&gt; The bibliography includes 165 references.

Understanding the driving factors and finding the pathway to mitigating carbon emissions in China's Yangtze River Delta region

Technological progress is an effective tool for controlling carbon emissions. However, because the connection between technological progress and carbon emissions remains under-theorized, the literature often discusses the overall effect of technological progress, ignoring the heterogeneity of technology. To better understand the driving factors of carbon emissions, we develop a new theoretical model based on the Green Solow model, in which technology is divided into production, energy conservation, and energy substitution technologies. Dynamic panel models are then applied to show the driving influence of different factors affecting carbon emissions in the Yangtze River Delta (YRD) region between 2000 and 2017. The results indicate that total technological progress is conducive to reducing carbon emissions. The heterogeneity analysis indicates a positive reduction effect on carbon emissions for energy substitution and energy conservation technologies, but not for production technology. Interestingly, production technology significantly drives carbon emissions. However, the results also suggest that to control carbon emissions, it is necessary to promote production technology. Further analysis suggests that production technology plays an important role in the effectiveness of energy conservation and energy substitution technologies in decreasing carbon emissions.

The energy conservation and emission reduction potentials in China's iron and steel industry: Considering the uncertainty factor

Energy conservation and emission reduction in China's iron and steel industry are crucial for mitigating its environmental pressures. However, uncertainties raise significant management risks when setting energy conservation and emission reduction pathways. Therefore, this paper explores the energy conservation and emission reduction potential in China's iron and steel industry. A 10,000-time Latin hypercube sampling is conducted to simulate the distribution of five types of uncertain factors. In addition, this study uses a Sobol’ sensitivity analysis method to recognize the most sensitive factor, and, in specific, analyzes the cost-effectiveness of the technologies via conservation supply curve. The results show that: (1) The uncertainty factors lead to significant fluctuate to the results. In particular, energy conservation will fluctuate by 18.24–40.77%, carbon mitigation by 28.96–55.34%, and SO2, NOx and PM mitigation effects will fluctuate by 48.32–79.53%, 22.12–51.77% and 23.92–50.03%, respectively. (2) Structure and equipment parameters are more the most sensitive to energy conservation and carbon mitigation targets, whose Sobol’ indices are beyond 0.45. End-of-pipe treatment technologies are more the most sensitive to SO2 and PM reduction targets with Sobol’ indices above 0.9. Penetration rates and equipment parameters are more the most sensitive to economic cost targets above 0.8. (3) In 2035, 33 energy conservation technologies and 34 emission reduction technologies will be cost-effective, and they can achieve 69.05–70.14% of energy conservation and 79.03–81.58% of emission reduction potentials, respectively. Based on these findings, this study proposes policy recommendations such as changing the raw material/product structure, upgrading equipment, cooperating actively, and introducing economic incentives and guidelines for technology application.

SUSTIE Core Engine: Efficient IoT Platform for Smart Facility Solutions with Gateway, Spatiotemporal Database, and Simulation Interface

The SUSTIE test facility was completed in 2020, and it facilitates to the development of energy-conservation technologies while contributing to the realization of more comfortable and energy-efficient indoor environments. The facility achieved the top rank of energy performance certification “Building-Housing Energy-efficiency Labeling System (BELS)” and wellness-office certification “Comprehensive Assessment System for Built Environment Efficiency-Wellness Office (CASBEE-WO)” in Japan. To accelerate research and evaluation, we propose an efficient Internet-of-things (IoT) platform called the SUSTIE Core Engine. The platform gathers data in real time, stores both design data and time-series data with coordinates, and act as simulation interface to satisfy three requirements of an IoT platform for smart facilities: an architecture that allows adding / removing functions without stopping operation, data management features for time-series / coordinates data, and common interface for simulations / controls. We implement the platform which covers the requirements to on-site system in the test facility, and evaluate the gateway, spatiotemporal database, and simulation interface. Our platform showed that it satisfies the three functional requirements of IoT platforms. Furthermore, it was shown that the database can obtain sufficient demonstrated for practical use.